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Have you taken a statistics class before? Depending on the subject of what you're testing, p < 1%, p < 5%, or p < 10% could all qualify as statistically significant. Anything over 10% is statistically insignificant, because the chances of the event happening by chance are far too great to be deemed different than than the control.
You probably weren't going to donate the 100 bucks anyways.
Wait, so you also believe that 5% of a population can be called "statistically significant"? If so, then you don't have a clue what statistically significant means. Instead of accusing me of not taking a stats course, you should know what you are talking about.
Once again, have you taken a statistics class before?
Clearly you do not understand how a test is performed. You don't test populations, you test sample sizes (of size n) because measuring entire populations is virtually impossible or impractical. Allow me to explain the most rudimentary concept of statistics you can possibly learn in a statistics class:
1. You need to test something.
2. You determine what population it applies to.
3. You acquire a sample from the population. This sample must not be very small, or else you increase the chances of the data and results being inaccurate.
4. You have a control group and a "treatment" group (the "treatment" group can be named anything, it is just the group that you are testing. The control group is a group not affected by your test, it is just something to compare your "treatment" group with after the test is performed.)
5. You randomly (ideally, simple random sample technique) assign members of the sample size to the two groups.
6. Perform the test.
7. Get p-value.
8. If p-value is less than determined alpha (as I posted earlier, 10% is the highest alpha), you can then assume the event is not due to chance, therefore it is statistically significant.
The most rudimentary concept in statistics. If you still do not understand it after taking a statistics course, well, good luck to you.
Oh and this is from Wikipedia. I could have just as easily pulled it from a stat textbook if I still had one on me. I suppose I should have let him look it up himself...but whatever. You probably weren't going to donate the 100 bucks anyways.
That's hilarious.
It is. The part that he bolded is the part that I quoted and linked to the wiki article, before he posted. I posted it above him and he acts like I never seen it. Bizarre.
Anyway, I know 5% is just the "conventional" or common level of significance. But doesn't that make it more appropriate in context?
... color blindness is probably statistically significant (5%) and this normal.
+/- one standard deviation from the mean on a normal curve includes 68% of the population. Once you get past one SD from the mean you are firmly in the realm of abnormal, since you are either in the top or bottom 16% with said characteristic.
But CC said it is defined in stat. Was he trying to hide a value judgement in math?
Total color blindness is not 1/20. Partial (especially minor) color blindness is probably statistically significant (5%) and this normal.
To be fair, ecofarm never said 5% of the population. That was Tucker Case. I don't believe that ecofarm meant 5% of the population, instead it meant you could prove the hypothesis that "partial (especially minor) color blindness isn't abnormal" if you used 5% as your level of significance.
Either way, you are not arguing the same thing. When something falls within two standard deviations (or 95%) it is considered normal. That is different than saying 95% of the population. Tucker Case argued that using the two standard deviations as a model, then color blindness would be considered normal, which is inaccurate, unless the statistical analysis was done on the entire population. I would wager that if you did a statistical analysis on a group (you choose the size), that color blindness would not fall within the two standard deviations.
He never said "5% of a population." I'm not sure if he was referring to a study with the color-blindness, but whether he was or not I'm pretty sure it was assumed that any data or hypothetical reasoning was from a sample, not a population.
This is what I first saw, which (at least in statistics) doesn't make much sense. Especially because 5% on each side of a normal curve is almost always the maximum any statistician would use in determining if something occurred by chance (normally) or due to something else.
First, he called a population "statistically significant" because they totaled 5%.
Second: a population is the group from which a sample is drawn. Since the normal distribution being discussed was not that of a sample, but that of the total population, we are clearly talking about populations. Your assumption is based on your ignorance of what was being discussed, as you have admitted ( I put your admission of ignorance in bold for you so that you are aware of that admission).
Third: He was obviously not referring to a study, which is abundantly clear by virtue of his answer to the very question "What study are you referring to?". See posts 739 and 740 for evidence of this. It's important to not be ignorant of what's being discussed before injecting yourself into a discussion.
Now who's never taken a stats class?
What does my statement that you quoted have to do with determining chance?
I don't believe that ecofarm meant 5% of the population, instead it meant you could prove the hypothesis that "partial (especially minor) color blindness isn't abnormal" if you used 5% as your level of significance.
Either way, you are not arguing the same thing. When something falls within two standard deviations (or 95%) it is considered normal. That is different than saying 95% of the population.
Tucker Case argued that using the two standard deviations as a model, then color blindness would be considered normal, which is inaccurate, unless the statistical analysis was done on the entire population.
And when tests are performed you are measuring whether or not something was due to chance.
Even if cutoffs are arbitrary, which you said after that quote, it still makes no sense because it doesn't apply like that. But this is getting old so I'm gonna call it a day with this thread.
BTW, there is a reason I chose the arbitrary cut off of one standard deviation when one wants to use a statistical definition of "normal" that relates to the topic at hand and it wasn't so that I could have homosexuality in the "abnormal" range (it might fall into that range if 2 standard deviations from the mean was used as well).
It was done that way so that a great many other things would fall into the "abnormal" range that people do not want to be considered abnormal.
Ultimately, it was to illustrate the asinine and fallacious nature of the "normal" debate, regardless of the definition of "normal" one chooses to use. Normal =/= good, abnormal =/= bad.
Basically, I'm saying that I understand the resistance to my choice to limit "normality" to one standard deviation from the mean. But it's important to remember that such resistance was the goal of my decision to limit it in this way.
Yeah the only problem I had with that was that significance level is determined somewhat arbitrarily, but that's only in tests. Since it wasn't a test, and therefore no significance level, it was just a matter of opinion, wasn't it? An educated opinion because you've taken statistics... But an opinion nonetheless?
This also shows an ignorance of what statistical significance is. Statistical significance would have no bearing on normal or abnormal under any circumstances.
CC your typical debate style of no substance and bullying and bogarting does NOT work with me...your twisting and fabricating others intent and meaning will not work either....you will NOT win this debate asking a perpetual question ad nausem. Ive answered your question several times...your twisting my response to fit your need to avoid answering mine is typical of your avoidance tactics..so again
Define how homosexuality is Normal.
Probably a dumb question but what constitutes normal, statistically? Within two standard deviations?
Statistics courses are for suckas. :lol:
They will give you a formula for figuring out the likelihood of a coin coming up heads after coming up tails 99 times in a row. That formula doesn't tell you the truth. The truth is it is still 50/50 heads/tails. The outcome is not dependent upon previous coin flips.
Semantics. Would it have appeased you if I had stated the hypothesis as "the chance of someone being partial (especially minor) color blind"? It's silly to ridicule people because of semantics.
As for rest about defining normal as +/- one deviation? Sounds like an opinion I could get behind. Honestly I have given up defining normal/abnormal for others a long time ago. My definition is pretty far out there in regards to abnormal compared to most.
The answer is: normal is arbitrary.
Depending on the hypothesis and the level of deviation the individual performing the hypothesis is looking for to define "within normal limits". Most times, this would be, as you said, two standard deviations, though sometimes it is one.
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